Security Scan Report: calendar.college.harvard.edu

Submitted: Nov 19, 2025, 9:30:10 PMCompleted: Nov 19, 2025, 9:32:52 PMpubliccompleted
Loading additional data...

Summary

This website contacted 75 IPs in 3 countries across 17 domains to perform 105 HTTP transactions. The main domain is calendar.college.harvard.edu.

Submitted URL: https://calendar.college.harvard.edu/event/cnns-abby-phillip

The Cisco Umbrella rank of the primary domain is #23,419 of the top 1 million websites

AI Security Verdict

Safe Website

Confidence: 95%

0
Risk Score

The page appears legitimate with no security concerns.

Safety Factors
Official Harvard institution domain
High Cisco Umbrella ranking indicating reputable site
Domain age information unavailable

Details

Page Title

CNN's Abby Phillip - Harvard College Calendar

Scan Type

public

Language

🇺🇸

English

(80% confidence)

Category

education

(90%)

Domain Information

The domain name 'calendar.college.harvard.edu' uses the sponsored educational top-level domain (.edu); it also runs on subdomain 'calendar.college'. Its registrable label 'harvard' stretches across 7 characters holding 2 vowels versus 5 consonants. It segments into one word: harvard. No strong language cues emerged from the frequency lists.

Screenshot

Security scan screenshot of https://calendar.college.harvard.edu/event/cnns-abby-phillip

Page Load Overview

2.08s
Total Load Time
105
HTTP Requests
17
Domains
4.6 MB
Total Size

Language Analysis

Primary Language

🇺🇸English
Code: en
Confidence:80%
Script:Latin
Direction:ltr

Detection Details

Language Code:en
Detection Confidence:80%
Script Type:Latin
HTML Lang Attribute:en
Text Length:2,985 chars
Detector Agreement:100%

Website Classification

Primary Category

education90% confidence
Type: spa
Method: structural

All Detected Categories

education
90%
corporate
50%

Detected Features

Search
Products
OG: website
Schema.org

Domain & IP Information

RequestsIP AddressLocationAS Autonomous System
20142.250.184.228United States
AS15169GOOGLE
1823.185.0.3United States
AS54113FASTLY
15142.250.186.42United States
AS15169GOOGLE
1213.107.213.44United States
AS8075MICROSOFT-CORP-MSN-AS-BLOCK
10216.239.32.36United States
AS15169GOOGLE
9142.250.185.74United States
AS15169GOOGLE
6142.250.186.136United States
AS15169GOOGLE
3172.217.18.3United States
AS15169GOOGLE
252.217.170.185Ashburn, Virginia, United States
AS16509AMAZON-02
2142.250.186.99United States
AS15169GOOGLE
10575--

Content Similarity HashesFor malware variant detection

TLSH (Trend Micro Locality Sensitive Hash)

Security-focused

Specialized for malware detection and similarity analysis

T1C9345BF263D461F49407D3F0D432ACE6716B18BB6A66D348F1ED8A916B0359CC94BC8B

ssdeep (Context Triggered Piecewise Hashing)

Context-aware

Detects similar content even with modifications

1536:gEXaDOMGNj3WNi6oH2DTkWYmId30twtb+ofE3cvbEFvzpKzpnRuA85bBbMifC2AO:sDOMGNj33UJ+oQUw893

sdhash (Similarity Digest Hashing)

High-precision

High-precision similarity detection for forensic analysis

sdhash:3:238055:TCYOnVNdA0UCRxsQCIFhEcoCQHfEEkXVVahGBIwYoEDIgoMngkMgQAZCOoJIUAGCPACCAANYgTlMVCKjugbKLAx0IBICgzAW

These hashes enable detection of similar websites and malware variants by comparing content similarity even when exact matches aren't found.

Image Hashes

Perceptual Hashes

Average Hash:003cfff3f3c3ffff
Perceptual Hash:ec12936c6c386d9b
Difference Hash:71d806a626063830
Wavelet Hash:0000d3c3c3c3ffdf
Color Hash:#53ac5a

Scan History

Scan history not available

Unable to load historical scan data